Supplementary Material for: Psoriasis and Dry Eye Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Psoriasis is a chronic inflammatory skin disease with potential systemic involvement. Some evidence suggests an increased risk of dry eye in patients with psoriasis. However, the relationship between these two conditions remains unclear. The aim of our study is to investigate the association between psoriasis and dry eye disease. Methods: This meta-analysis was registered in PROSPERO (CRD42020199445) and adhered to MOOSE checklist and PRISMA guidance for all processes. PubMed, Embase, Web of Science, and Cochrane databases were searched for studies examining the association between psoriasis and dry eye disease from inception to December 13, 2020. The primary outcome was the prevalence of dry eye disease in patients with psoriasis relative to controls. The secondary outcomes were the Schirmer I test score, tear film breakup time (TBUT), and ocular surface disease index (OSDI). The risk of bias of the selected studies was assessed using the Newcastle-Ottawa Scale. Results: The meta-analysis showed a significant association between dry eye disease and psoriasis (OR, 8.49; 95% CI, 3.34–21.58). Moreover, patients with psoriasis had a significantly lower Schirmer I test score (MD, −2.80; 95% CI, −4.07 to −1.52), shorter TBUT (MD, −4.12; 95% CI, −5.22 to −3.02), and higher OSDI (MD, 20.15; 95% CI, 6.24–34.05; p < 0.01), compared to controls. Conclusions: The current evidence supports an association between dry eye disease and psoriasis. These results suggest ophthalmologic assessment for the early recognition and management of dry eye in patients with psoriasis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.751 | 0.049 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".